SimurgAI Lab's repositories
tooth-detection-and-numbering-in-panoramic-radiographs
The tooth numbering module classifies and numbering dental objects detected as a result of segmentation according to the FDI notation used universally by dentists.
an-enhanced-tooth-segmentation-in-bitewing-radiographs
This study was published in 2022 in a scientific journal with SCI-Expanded index. The tooth numbering module uses the FDI notation, which is widely used by dentists, to classify and number dental items found as a result of segmentation. The performance of the Mask R–CNN method used has been proven by comparing it with other state-of-the-art methods.
mask-rcnn-implementation-with-custom-dataset
Implementation of Mask R-CNN architecture, one of the object recognition architectures, on a custom dataset.
automatic-dental-segmentation-module
In this study, DentiAssist, a web-based radiological image analysis and labeling application supported by artificial intelligence, was developed for the education of dentistry students.
installation-guide-of-maskrcnn
Mask R-CNN creates a high-quality segmentation mask in addition to the Faster R-CNN network. In addition to class labels and scores, a segmentation mask is created for the objects detected by this neural network. In this repository, using Anaconda prompt step by step Mask R-CNN setup is shown.
faster-r-cnn-tensorflow-api-custom
Faster R-CNN with Tensorflow Object Detection API for Custom Dataset.